Papers
Topics
Authors
Recent
Search
2000 character limit reached

The Impact of 2D and 3D Gamified VR on Learning American Sign Language

Published 14 May 2024 in cs.HC | (2405.08908v1)

Abstract: Sign language has been extensively studied as a means of facilitating effective communication between hearing individuals and the deaf community. With the continuous advancements in virtual reality (VR) and gamification technologies, an increasing number of studies have begun to explore the application of these emerging technologies in sign language learning. This paper describes a user study that compares the impact of 2D and 3D games on the user experience in ASL learning. Empirical evidence gathered through questionnaires supports the positive impact of 3D game environments on user engagement and overall experience, particularly in relation to attractiveness, usability, and efficiency. Moreover, initial findings demonstrate a similar behaviour of 2D and 3D games in terms of enhancing user experience. Finally, the study identifies areas where improvements can be made to enhance the dependability and clarity of 3D game environments. These findings contribute to the understanding of how game-based approaches, and specifically the utilisation of 3D environments, can positively influence the learning experience of ASL.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (51)
  1. The acquisition of american sign language. In The crosslinguistic study of language acquisition, pages 881–938. Psychology Press, 2017.
  2. User-defined hand gesture interface to improve user experience of learning american sign language. In International Conference on Intelligent Tutoring Systems, pages 479–490. Springer, 2023.
  3. Deaf individuals’ bilingual abilities: American sign language proficiency, reading skills, and family characteristics. 2011.
  4. Towards student behaviour simulation: a decision transformer based approach. In International Conference on Intelligent Tutoring Systems, pages 553–562. Springer, 2023.
  5. A survey of collaborative reinforcement learning: interactive methods and design patterns. In Proceedings of the 2021 ACM Designing Interactive Systems Conference, pages 1579–1590, 2021.
  6. A case of specific language impairment in a deaf signer of american sign language. The Journal of Deaf Studies and Deaf Education, 22(2):204–218, 2017.
  7. Sim-gail: A generative adversarial imitation learning approach of student modelling for intelligent tutoring systems. Neural Computing and Applications, 35(34):24369–24388, 2023.
  8. The adoption of students’ hedonic motivation system model to gamified learning environment. Journal of theoretical and applied electronic commerce research, 14(3):156–167, 2019.
  9. Gamification and student motivation. Interactive learning environments, 24(6):1162–1175, 2016.
  10. Exploring the potential of immersive virtual environments for learning american sign language. In European Conference on Technology Enhanced Learning, pages 459–474. Springer, 2023.
  11. Personalization of gamification-elements in an e-learning environment based on learners’ motivation. In 2016 8th International symposium on telecommunications (IST), pages 637–642. IEEE, 2016.
  12. Samaa M Shohieb. A gamified e-learning framework for teaching mathematics to arab deaf students: Supporting an acting arabic sign language avatar. Ubiquitous Learning: An International Journal, 12(1):55–70, 2019.
  13. Comparative efficacy of 2d and 3d virtual reality games in american sign language learning. In The 31st IEEE Conference on Virtual Reality and 3D User Interfaces. Newcastle University, 2024.
  14. Impact of personalised ai chat assistant on mediated human-human textual conversations: Exploring female-male differences. In Companion Proceedings of the 29th International Conference on Intelligent User Interfaces, pages 78–83, 2024.
  15. The effects of gamification in online learning environments: A systematic literature review. In Informatics, volume 6, page 32. MDPI, 2019.
  16. Contextual gamification of social interaction – towards increasing motivation in social e-learning. In Elvira Popescu, Rynson W. H. Lau, Kai Pata, Howard Leung, and Mart Laanpere, editors, Advances in Web-Based Learning – ICWL 2014, pages 116–122, Cham, 2014. Springer International Publishing.
  17. Motivational gamification strategies rooted in self-determination theory for social adaptive e-learning. In Alessandro Micarelli, John Stamper, and Kitty Panourgia, editors, Intelligent Tutoring Systems, pages 294–300, Cham, 2016. Springer International Publishing.
  18. Copycat: an american sign language game for deaf children. In Face and Gesture 2011, pages 647–647. IEEE Computer Society, 2011.
  19. An educational game to teach numbers in brazilian sign language while having fun. Computers in Human Behavior, 107:105825, 2020.
  20. Work-in-progress-gamifying the process of learning sign language in vr. In 2022 8th International Conference of the Immersive Learning Research Network (iLRN), pages 1–3. IEEE, 2022.
  21. Smile: an immersive learning game for deaf and hearing children. In ACM SIGGRAPH 2007 educators program, pages 17–es. 2007.
  22. Enhancing user experience in chinese initial text conversations with personalised ai-powered assistant. In Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, CHI EA ’24, New York, NY, USA, 2024. Association for Computing Machinery.
  23. Developing and evaluating a novel gamified virtual learning environment for asl. In IFIP Conference on Human-Computer Interaction, pages 459–468. Springer, 2023.
  24. Integrating lstm and bert for long-sequence data analysis in intelligent tutoring systems. arXiv preprint arXiv:2405.05136, 2024.
  25. Lbkt: a lstm bert-based knowledge tracing model for long-sequence data. In 20th International Conference on Intelligent Tutoring Systems: Generative Intelligence and ITS (10/06/24 - 13/06/24), June 2024.
  26. ASL Sea Battle: Gamifying Sign Language Data Collection. In Proc. CHI-HFCS, pages 1–13, 2021.
  27. Zhaoxing Li. Deep Reinforcement Learning Approaches for Technology Enhanced Learning. PhD thesis, Durham University, 2023.
  28. Broader and deeper: A multi-features with latent relations bert knowledge tracing model. In European Conference on Technology Enhanced Learning, pages 183–197. Springer, 2023.
  29. Applying the user experience questionnaire (UEQ) in different evaluation scenarios. In International Conference of Design, User Experience, and Usability, pages 383–392. Springer, 2014.
  30. Sign language transformers: Joint end-to-end sign language recognition and translation. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 10023–10033, 2020.
  31. Sign language recognition, generation, and translation: An interdisciplinary perspective. In Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility, pages 16–31, 2019.
  32. Iterative alignment network for continuous sign language recognition. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 4165–4174, 2019.
  33. Mediapipe hands: On-device real-time hand tracking. arXiv:2006.10214, 2020.
  34. Deep learning-based sign language recognition system for static signs. Neural computing and applications, 32:7957–7968, 2020.
  35. Skeleton aware multi-modal sign language recognition. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 3413–3423, 2021.
  36. 3d sign language recognition using spatio temporal graph kernels. Journal of King Saud University-Computer and Information Sciences, 34(2):143–152, 2022.
  37. Human-centered design for a sign language learning application. In Proc. PETRAE, pages 1–5, 2020.
  38. Effect of automatic sign recognition performance on the usability of video-based search interfaces for sign language dictionaries. In Proceedings of the 21st International ACM SIGACCESS Conference on Computers and Accessibility, pages 56–67, 2019.
  39. Effect of sign-recognition performance on the usability of sign-language dictionary search. ACM Transactions on Accessible Computing (TACCESS), 14(4):1–33, 2021.
  40. Design and evaluation of hybrid search for american sign language to english dictionaries: Making the most of imperfect sign recognition. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, pages 1–13, 2022.
  41. Kinect-sign: teaching sign language to “listeners” through a game. In Innovative and Creative Developments in Multimodal Interaction Systems: 9th IFIP WG 5.5 International Summer Workshop on Multimodal Interfaces, eNTERFACE 2013, Lisbon, Portugal, July 15–August 9, 2013. Proceedings 9, pages 141–159. Springer, 2014.
  42. A new robotic platform for sign language tutoring: Humanoid robots as assistive game companions for teaching sign language. International Journal of Social Robotics, 7:571–585, 2015.
  43. American sign language recognition using deep learning and computer vision. In International Conference on Big Data, pages 4896–4899. IEEE, 2018.
  44. Mary Jane C Samonte. An assistive technology using fsl, speech recognition, gamification and online handwritten character recognition in learning statistics for students with hearing and speech impairment. In Proc. ICFET, pages 92–97, 2020.
  45. Using Serious Games for Learning British Sign Language Combining Video, Enhanced Interactivity, and VR Technology. Journal of Universal Computer Science, 26(8):996–1016, 2020.
  46. Opencv. Dr. Dobb’s journal of software tools, 3:120, 2000.
  47. Why Python. Python. Python Releases for Windows, 24, 2021.
  48. Tensorflow distributions. arXiv:1711.10604, 2017.
  49. The role of tutoring in problem solving. Journal of child psychology and psychiatry, 17(2):89–100, 1976.
  50. Determining what individual sus scores mean: Adding an adjective rating scale. Journal of usability studies, 4(3):114–123, 2009.
  51. Construction of a Benchmark for the User Experience Questionnaire (UEQ). International Journal of Interactive Multimedia and Artificial Intelligence, 4:40–44, June 2017.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.

Tweets

Sign up for free to view the 2 tweets with 0 likes about this paper.